An Astronomical Pattern-Matching Algorithm for Automated Identification of Whale Sharks

Abstract

The largest shark species alive today, whale sharks (Rhincodon typus) are rare and poorly studied. Directed fisheries, high value in international trade, a highly migratory nature, and generally low abundance make this species vulnerable to exploitation. Mark- and-recapture studies have provided our current understanding of whale shark demographics and life history, but conventional tagging has met with limited success. To aid in conservation and management efforts, and to further our knowledge of whale shark biology, an identification technology that maximizes the scientific value of individual sighting is needed.